Dynamic sound masking based on monitoring biosignals and environmental noises

ABSTRACT

Aspects of the present disclosure provide methods, apparatuses, and systems for closed-loop sleep protection and/or sleep regulation. According to an aspect, sleep disturbing noises are predicted and a biosignal parameter is measured to dynamically mask predicted disturbing environmental noises in the sleeping environment with active attenuation. Environmental noises in a sleeping environment of a subject are detected, input, or predicted based on historical data of the sleeping environment collected over a period of time. The biosignal parameter is used to determine sleep physiology of a subject. Based on the environmental noises in the sleeping environment and the determined sleep physiology, the noises are predicted to be disturbing or non-disturbing noises. For predicted disturbing noises, one or more actions are taken to regulate sleep and avoid sleep disruption by using sound masking prior to or concurrently with the occurrence of the predicted disturbing noises.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to co-pending U.S. Non-Provisionalpatent application Ser. No. 16/278,322, entitled “DYNAMIC MASKING WITHDYNAMIC PARAMETERS”, filed Feb. 18, 2019. The aforementioned relatedpatent application is herein incorporated by reference in its entirety.

Aspects of the present disclosure generally relate to closed-loopmethods, devices, and systems for regulating or protecting a subject'ssleep.

Disruptions to a subject's sleep may result in poor sleep and negativelyaffect the subject's health. Sleep disruptions may be caused byenvironmental or ambient noises in the sleeping environment of thesubject that interrupt the subject's sleep. To try to block orcompensate for such sleep disturbing noises, a static or blanket maskingsound may be output in the subject's sleeping environment. However, thestatic masking sound is typically played throughout the entire timeperiod the subject is sleeping at a constant, unchanging volume andfrequency. Depending on the varying volumes and frequencies of theenvironmental noises and the subject's sleep physiology, the staticmasking sound may be ineffective at compensating for some sleepdisturbing noises, or may itself disrupt the subject's sleep. As such, aneed exists for dynamically masking individual environmental noises in asubject's sleeping environment in a manner that is tailored to thesubject.

SUMMARY

Aspects of the present disclosure provide methods, apparatuses, andsystems for closed-loop sleep protection and/or sleep regulation.According to an aspect, potential sleep disturbing noises are predictedand biosignal parameters of a subject are measured to dynamically maskpredicted disturbing noises in the sleeping environment with activeattenuation. Based on the predicted disturbing noises and the measuredbiosignal parameters, one or more actions are taken to regulate sleepand avoid sleep disruption by sound masking prior to or concurrentlywith the occurrence of the predicted disturbing noises.

According to one aspect, an audio device comprises at least onebiosensor for measuring at least one biosignal parameter of a subjectand a processing unit. The processing unit is configured to predict atiming of when the environmental noises will occur, and predict whetherthe environmental noises will disturb the subject's sleep based on theat least one measured biosignal parameter and the predicted timing ofthe environmental noises to identify predicted disturbing noises. Theaudio device further comprises at least one speaker for outputting amasking sound prior to occurrence of the predicted disturbing noises.

The processing unit may be further configured to adjust the maskingsound based on the at least one measured biosignal parameter and thepredicted disturbing noises. Adjusting the masking sound may compriseadjusting at least one of a spectral content of the masking sound or asound pressure level of the masking sound. The processing unit may beconfigured to predict whether the environmental noises will disturb thesubject's sleep based on the at least one measured biosignal parameterand the predicted timing of the environmental noises further identifiesnon-disturbing noises to the subject's sleep. The at least one speakermay be configured to refrain from outputting a masking sound inanticipation of the identified non-disturbing noises. The at least onespeaker may be configured to gradually increase outputting the maskingsound prior to the predicted disturbing noises occurring, and togradually decrease outputting the masking sound after the predicteddisturbing noises have stopped.

The audio device may further comprise at least one microphone formonitoring environmental noises in a vicinity of the audio device. Theat least one microphone may be configured to monitor the environmentalnoises over a time period to determine reoccurring noises and todetermine timing and frequency of the environmental noises. Theprocessing unit may be further configured to receive input from thesubject regarding known disturbing sounds to mask. The speaker may befurther configured to output a masking sound prior to occurrence of theknown disturbing sounds. The at least one biosignal parameter maycomprise at least one of: a heart rate, heart rate variability,respiration rate, electroencephalogram (EEG), electrooculogram (EOG),electromyogram (EMG), or motion of the subject.

In another aspect, a method for regulating a sleep pattern of a subjectcomprises measuring at least one biosignal parameter of the subjectwhile the subject is sleeping in the sleeping environment. The biosignalparameter is indicative of a current sleep condition of the subject. Themethod further comprises predicting whether a potentially disturbingnoise will disturb the subject based on the current sleep condition andthe potentially disturbing noise to identify a predicted disturbingnoise, and outputting a masking sound prior to an occurrence of thepredicted disturbing noise.

The method may further comprise adjusting the masking sound prior tooutputting the masking sound based on the sleep condition of the subjectand the predicted disturbing noise. Adjusting the masking sound maycomprise adjusting at least one of: a spectral content of the maskingsound or a sound pressure level of the masking sound. The masking soundmay be output immediately prior to the occurrence of the predicteddisturbing noise. Outputting the masking sound may comprise graduallyincreasing the masking sound over a first time period prior to theoccurrence of the predicted disturbing noise, and gradually decreasingthe masking sound over a second time period after the predicteddisturbing noise has stopped.

The method may further comprise receiving, from the subject, at leastone known disturbing noise to mask prior to outputting the maskingsound. The method may further comprise monitoring the at least onebiosignal parameter of the subject over a time period to gatherhistorical sleep data of the subject. Predicting when the noise willdisturb the subject may be further based on the historical sleep data.The method may further comprise monitoring a sleeping environment of thesubject for a potentially disturbing noise over a time period via amicrophone.

In yet another aspect, an audio system comprises at least one biosensorfor measuring at least one biosignal parameter of a subject over a firsttime period. One or more values of the biosignal parameter areindicative of a sleep condition of the subject over the first timeperiod. The audio system further comprises a processing unit configuredto predict a timing of when the reoccurring ambient noises will occur,predict whether the reoccurring ambient noises will disturb thesubject's sleep based on the at least one measured biosignal parameterand the predicted timing of the reoccurring ambient noises to identifypredicted disturbing noises, and adjust a masking sound based on the atleast one measured biosignal parameter and the predicted disturbingnoises. The audio system further comprises at least one speakerconfigured to gradually increase outputting the masking sound prior tothe predicted disturbing noises occurring, and to gradually decreaseoutputting the masking sound after the predicted disturbing noises arecomplete.

A first device may comprise the at least one biosensor. The first devicemay be a wearable device. The first device may further comprise the atleast one speaker. The audio system may further comprise at least onemicrophone for monitoring ambient noises over a second time period todetermine reoccurring ambient noises. A second device may comprise theat least one microphone. The second device may be a bedside unit. Thesecond device may further comprise the at least one speaker.

The audio system may further comprise a transceiver configured toreceive input from the subject regarding at least one noise thatdisturbed the subject's sleep. The processing unit may be configured topredict a timing of when the at least one noise will occur and furtheradjust the masking sound based on the predicted timing. Input from thesubject may comprise a recording of the at least one noise.

All examples and features mentioned herein can be combined in anytechnically possible manner.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example of sleep fragility as a function ofstimulus intensity and EEG alpha content.

FIG. 2 illustrates an example audio system in a sleeping environment.

FIG. 3 illustrates example components of an audio device.

FIG. 4 illustrates an example method for dynamically and proactivelymasking potential sleep disturbing noises in a sleeping environment.

DETAILED DESCRIPTION

A sleep assistance device may include features to perform any one ofpreparing a subject to fall asleep, initiating the subject's sleep,protecting the subject's sleep, and selectively disrupting the subject'ssleep. Aspects of the present disclosure provide methods, devices, andsystems configured to collect biometric information associated with asubject and adaptively alter a sound output based on the collectedinformation.

FIG. 1 illustrates an example of sleep fragility as a function ofstimulus intensity and EEG alpha content. While the example demonstratessleep fragility as a function of stimulus intensity and EEG alphacontent, other mechanisms may be used to detect sleep stages, either incombination with EEG or alone, such as EOG, accelerometer, RPM, corticalarousals, HRV, PAT/PPG, etc., as discussed further below. A subject'sprobability of sleep disruption is based, in part, on a condition orphysiology of the subject's sleep. A condition of sleep refers to, forexample, how deeply the subject is sleeping. As used herein, sleepcondition may refer to as sleep physiology, sleep fragility, sleepvulnerability, or terms referring to the likelihood of sleep beingdisrupted.

In an example, the condition may be associated with sleep stages. StageN3 sleep is the deepest type of non-rapid eye movement (NREM) sleep.Stage N2 sleep is lighter and more fragile than stage N3 sleep. Asillustrated in FIG. 1, for a same sound intensity, a subject has anincreased likelihood of sleep disruption when in stage N2 sleep thanwhen in stage N3 sleep.

In an aspect, biometric information collected from the subject is usedto approximate the subject's sleep condition. The sleep condition isused to predict the likelihood the subject's sleep may be disrupted. Theeffect of ambient or environmental noises on a sleeping subject variesbased on the subject's sleep condition as well as the subject'sindividual sensitivities to such ambient or environmental noises. A samesound is less likely to disrupt a subject in deep sleep as compared to asubject whose sleep is already compromised. Sounds may be adjustedresponsive to the condition of the subject's sleep so that a same soundmay be masked more when the subject's sleep is compromised as comparedto when the subject's sleep is less compromised.

Masking sounds are adjusted based on the subject's determined sleepcondition and the environmental noise in the vicinity of the subject.The sound is altered in an effort to adaptively regulate and protect thesubject's sleep. As will be described in more detail herein, the soundis altered by one or more of adjusting a sound pressure level (SPL) of amask, adjusting a spectral content of a mask, or adjusting active noisereduction (ANR) bandwidth and level to mask (i.e., attempt to cover upthe perception of) environmental noise based on the subject's determinedsleep condition. According to aspects, the masking reduces the perceivedloudness from the environment even if the masking does not remove theperception of environmental noise entirely. While the term “maskingsound” is used throughout, the described methods, apparatuses, andsystems are not limited to outputting and adjusting only masking sounds.The term “masking sound” as used herein includes other such sounds to beplayed in a sleeping environment, such as soothing sounds, audiotherapeutics, relaxation soundtracks, entrainment soundtracks, etc.

Currently, static masking sounds such as shaped noise or oceansoundscapes attempt to help subjects fall and stay asleep; however,subjects may not enjoy listening to sound while falling asleep andsubjects may be exposed to long durations of potentially harmful soundlevels. Furthermore, based on the subject's changing sleep conditionthroughout a sleep period, these static masking sounds may disrupt thesubject's sleep. Dynamically adjusting the masking properties based onthe sleep condition and the environmental noise mitigates these issuesby playing masking sounds to mask at reduced levels or altered spectrawhen able, based on sleep condition, external noise, or both at a giventime. Therefore subjects are exposed to less noise, reducing potentialacoustic trauma to the auditory system, as masking is played at a soundlevel necessary to mask external noise in view of a sleep condition. Acorrect amount of masking is presented to help prevent sleepdisturbance.

FIG. 2 illustrates an example audio system 200 in a sleepingenvironment, according to an aspect. The audio system 200 may be used todynamically mask predicted disturbing environmental noises in thesleeping environment with active attenuation. In an example, the audiosystem 200 is configured to anticipate potentially disturbing noises ina subject's sleeping environment, collect biometric information of thesubject, and output adjusted sounds based on the potentially disturbingnoises and the biometric information collected in an effort to regulatethe subject's sleep prior to or concurrently with the potentiallydisturbing noises occurring. The adjusted sounds may be masking soundswith an adjusted SPL and/or adjusted spectral content. Additionally oralternatively, the sounds may entrain breathing in an effort to regulatesleep. Additionally or alternatively, the audio system 200 may adjust anamount and timing of ANR based on the determined sleep condition andenvironmental noise in an effort to protect sleep.

The audio system 200 includes headphones 204 and a smartwatch 206, whichare shown as being worn by a subject. A headphone 204 refers to a devicethat fits around, on, or in an ear and that radiates acoustic energyinto the ear canal. Headphones 204 are sometimes referred to asearphones, earpieces, headsets, earbuds, or sport headphones, and can bewired or wireless. The headphones 204 may comprise one or more of: aprocessing unit, a transceiver, one or more biosensors, one or morespeakers, and one or more microphones. The headphones 204 may comprisean interface configured to receive input from a subject. A smartwatch206 may be any type of wearable computer designed to be worn on a wristof a subject, such as a fitness tracker. The smartwatch 206 may compriseone or more of: a processing unit, a transceiver, one or morebiosensors, one or more speakers, and one or more microphones. Thesmartwatch 206 may comprise an interface configured to receive inputfrom a subject.

The audio system 200 further includes a bedside unit 208 and asmartphone 202. The smartphone 202 may be a mobile phone, tablet,phablet, or laptop computer. The smartphone 202 may comprise one or moreof: a processing unit, a transceiver, one or more biosensors, one ormore speakers, and one or more microphones. The smartphone 202 maycomprise an interface configured to receive input from a subject. Thebedside unit 208 may be a stationary smart device, such as a smartspeaker. The bedside unit 208 may have any shape and size capable offitting on a surface in the sleeping environment, such as a dresser,desk, or night table. For instance, the bedside unit 208 may be square,round, rectangular, pyramidal, or oval, as well as short, tall, wide,thick, or thin. The bedside unit 208 may comprise one or more of: aprocessing unit, a transceiver, one or more biosensors, one or morespeakers, and one or more microphones. The bedside unit 208 may comprisean interface configured to receive input from a subject.

The headphones 204, the smartwatch 206, the bedside unit 208, and thesmartphone 202 may each include any wired or wireless communicationmeans suitable for use with any other device 202-208 disposed in thesleeping environment, such as WiFi, Bluetooth, Near Field Communications(NFC), USB, micro USB, or any suitable wired or wireless communicationstechnologies known to one of ordinary skill in the art. For example, theheadphones 204 may comprise one or more speakers while the bedside unit208 comprises one or more microphones in communication with the one ormore speakers of the headphones 204. Furthermore, the audio system 200may include one or more of the devices 202-208, and is not required toinclude each device 202-208 shown. Thus, each device 202-208 in theaudio system 200 may be optionally included, and only one device 202-208is needed to dynamically mask environmental noises.

The devices 202-208 of the audio system 200, either alone or incombination, are configured to: monitor the sleeping environment forpotentially disturbing noises, collect historical data on potentiallydisturbing noises in the vicinity of a subject's sleeping environment,receive input regarding potentially disturbing or non-disturbing noises,determine one or more sound parameters of the potentially disturbingnoises, measure one or more biosignal parameters of a subject, collecthistorical data on a subject's biosignal parameters, predict a timing ofwhen the potentially disturbing noises will occur; predict when a noisewill disturb the subject's sleep, refrain from outputting a maskingsound in anticipation of identified non-disturbing noises, adjust amasking sound based on the predicted disturbing noises and the measuredone or more biosignal parameters in anticipation of predicted disturbingnoises, and output the masking sound prior to or concurrently with apredicted disturbing noise occurring in the sleeping environment.

FIG. 3 illustrates example components of an audio device 300, inaccordance with certain aspects of the present disclosure. According toan example, the audio device 300 is a wireless wearable audio device.The audio device 300 may be used in an audio system, such as the audiosystem 200 of FIG. 2. For instance, the audio device 300 may be anydevice 202-208 in the audio system 200 of FIG. 2. In one example, theaudio device 300 is the headphones 204 of FIG. 2. The audio device 300may be used to dynamically mask predicted disturbing environmentalnoises in the sleeping environment with active attenuation. In anexample, the audio device 300 is configured to anticipate potentiallydisturbing noises in a subject's sleeping environment, collect biometricinformation of the subject, and output adjusted sounds based on thepotentially disturbing noises and the biometric information collected inan effort to regulate the subject's sleep prior to or concurrently withthe potentially disturbing noises occurring. The adjusted sounds may bemasking sounds with an adjusted SPL, adjusted timing, and/or adjustedspectral content. Additionally or alternatively, the sounds may entrainbreathing in an effort to regulate or protect sleep. Additionally oralternatively, the audio device 300 may adjust an amount and timing ofANR based on the determined sleep condition and environmental noise inan effort to protect sleep.

The audio device 300 includes a memory and processor 302, communicationunit 304, a transceiver 306, a biosensor 312, and an audio outputtransducer or speaker 308. The memory may include Read Only Memory(ROM), a Random Access Memory (RAM), and/or a flash ROM. The memorystores program code for controlling the memory and processor 302. Thememory and processor 302 control the operations of the audio device 300.Any or all of the components in FIG. 3 may be combined intomulti-function components.

The processor 302 controls the general operation of the audio device300. For example, the processor 302 performs process and control foraudio and/or data communication. In addition to the general operation,the processor 302 outputs adjusted sounds in an effort to regulate asubject's sleep. The processor 302 is configured to measure, receive,calculate, or detect at least one biosignal parameter of the subject.The processor 302 is configured to utilize the biosignal parameter alongwith the subject's historical sleep data in an effort to determine acurrent sleep condition of the subject. The processor 302 is configuredto determine, detect, or receive information associated with theenvironmental noise in the vicinity of the subject. The processor 302 isconfigured to adjust sound based on the subject's sleep condition andthe environmental noise. In combination with the audio output transducer308, the processor 302 is configured to output the adjusted sounds. Theprocessor 302 may be further configured to receive input from a subject,such as input regarding both disturbing noises to mask andnon-disturbing noises to refrain from masking. In at least one example,the processor 302 is disposed on another device in an audio system, suchas a smartphone, and is in communication with the audio device 300.

In one embodiment, the processor 302 is further configured to determinewhen a predetermined total noise exposure level is reached or will soonbe reached. In response to the total exposure level being reached, theprocessor 302 may be configured to cease outputting or adjusting maskingsounds in response to disturbing noises in an effort to protect asubject's auditory system. In an embodiment where the processor 302 isconfigured to determine the total exposure level is approaching or willsoon be reached, the processor 302 may be configured to reduceoutputting or adjusting masking sounds in response to disturbing noisesto prevent the total exposure level from being reached and to helpprotect a subject's auditory system.

The communication unit 304 facilitates a wireless connection with one ormore other wireless devices, such as with other devices in an audiosystem. For example, the communication unit 304 may include one or morewireless protocol engines such as a Bluetooth engine. While Bluetooth isused as an example protocol, other communication protocols may also beused. Some examples include Bluetooth Low Energy (BLE), NFC, IEEE802.11, WiFi, or other local area network (LAN) or personal area network(PAN) protocols. The audio device 300 may receive audio files wirelesslyvia the communication unit 304. Additionally or alternatively, thecommunication unit 304 may receive information associated with asubject's biosignal parameters, obtained via a contactless sensor.Examples of contactless sensors include a radio frequency (RF) sensor oran under-bed accelerometer.

The transceiver 306 transmits and receives information via one or moreantennae to exchange information with one or more other wirelessdevices. The transceiver 306 may be used to communicate with otherdevices in an audio system, such as a bedside unit, a smartphone, and/ora smartwatch. The transceiver 306 is not necessarily a distinctcomponent.

The audio device 300 includes the audio output transducer 308, which maybe also known as a driver or speaker. In some examples, more than oneoutput transducer is used. The transducer 308 (that may be part of amicrophone) converts electrical signals into sound and converts soundinto electrical signals. The transducer 308 is configured to dynamicallyoutput masking sounds. The transducer 308 outputs audio signals,including adjusted audio signals in an effort protect the subject'ssleep. For example, the transducer 308 may be configured to adjust audiosignals in response to a subject's biosignal parameters. In at least oneexample, the transducer 308 is disposed on another device in an audiosystem, such as a bedside unit, and is in communication with the audiodevice 300.

The audio device 300 optionally includes one or more microphones 310. Inan aspect, the microphones 310 are used to detect environmental noisesin the vicinity of the audio device 300, and convert the detected noiseinto electrical signals. In combination with the memory and processor302, the microphones 310 may be configured to record, track, store, andanalyze environmental noises in the vicinity of the audio device 300over a period of time. The sound parameters or properties of theenvironmental noises, such as the timing, decibel level, and frequency,may be then determined to collect historical data of noises detected inthe vicinity of the audio device 300 or sleeping environment. In atleast one example, one or more microphones 310 are disposed on anotherdevice in an audio system, such as a bedside unit, and are incommunication with the audio device 300.

The audio device 300 optionally includes one or more biosensors 312 usedto determine, sense, measure, monitor, or calculate a biosignalparameter of a subject wearing the audio device 300. According to anexample, the biosensor 312 is one of a photoplethysmography (PPG)sensor, electroencephalogram (EEG) sensor, electrocardiogram (ECG)sensor, electrooculogram (EOG) sensor, electromyogram (EMG) sensor,accelerometer, a microphone, or other suitable devices. The biosensor312 may be any sensor configured to determine, sense, measure, monitor,or calculate a subject's biosignal parameter(s). The biosignalparameter(s) may comprise at least one of: a heart rate, heart ratevariability, respiration rate, EEG, EOG, EMG, motion of the subject, orother suitable parameters. The biosensor 312 may be further configuredto monitor a subject's biosignal parameters over a period of time tocollect historical data of the biosignal parameters. The biosignalparameters may be used to determine a sleep condition or sleepphysiology of the subject. Based on the sleep condition, an arousalthreshold may be determined. The sleep condition may be determined basedon one or more of personalized sleep data or historical sleep datacollected using a subset of society, or both.

According to an aspect when the audio device 300 is headphones, only oneearpiece (ear tip, ear cup) of the audio device 300 includes thebiosensor 312. In an aspect, neither earpiece includes a biosensor 312.Instead, a biosensor 312, not on the audio device 300, may remotelydetect a biosignal parameter of the subject. In an example, thebiosensor 312 detects fluctuations in small arteries (i.e., arterioles)with a sensor, for example, on the finger to determine blood vesseldynamics, which may help to determine the subject's sleep fragility. Inan example, the biosensor 312 detects a subject's heartrate or heartrate variability (HRV) with a sensor disposed on the wrist, such as byutilizing a smartwatch. In an example, the biosensor 312 may be acontactless biosensor. The contactless biosensor is configured to reportdetected biosignal parameters to the processor 302, for example, via thecommunication unit 304. In at least one example, the biosensor 312 isdisposed on another device in an audio system, such as a smartwatch, andis in communication with the audio device 300.

FIG. 3 illustrates communication between certain modules of an exampleaudio device 300; however, aspects of the disclosure are not limited tothe specific illustrated example. According to aspects, any module302-312 is configured to communicate with any other module in the audiodevice 300. In one example, all modules 302-312 are connected to andcommunicate with each other.

FIG. 4 illustrates an example method 400 for dynamically and proactivelymasking potential sleep disturbing noises in a sleeping environment.Method 400 may be implemented utilizing the audio system 200 of FIG. 2and/or the audio device 300 of FIG. 3.

At 402, a sleeping environment is optionally monitored for potentialsleep disturbing noises. The sleeping environment may be monitored usinga microphone, such as the microphone 310 of FIG. 3. The sleepingenvironment may be monitored over a period of time to determinereoccurring noises and to determine sound parameters of the detectedenvironmental noises. The microphone may detect various sound parametersof the detected noises, such as the decibel level, the onset and offset,the rate, the timing, and the frequency. In combination with a memoryand processor, the microphone may detect environmental noises over aperiod of time, allowing historical data of the noises in the subject'ssleeping environment to be collected and analyzed. The historical dataof the noises in the subject's sleeping environment may be used torefine the dynamic masking via a learning algorithm.

At 404, one or more potentially disturbing noises are optionally inputinto a processing unit. A processing unit, such as the processor 302 ofFIG. 3, or a smart device, such as the smartphone 202 or smartwatch 206of FIG. 2, may be configured to receive input from the subject regardingat least one noise that is known to disturb the subject's sleep. Thesubject may further input one or more non-disturbing noises that thesubject does not wish be masked. For example, the subject may wish tohear a baby crying, and may input a baby's crying as a non-disturbingnoise to refrain from masking. Additionally, the subject may inputvarious time periods of when to mask or refrain from maskingenvironmental noises. The subject inputting potentially disturbingnoises to mask and non-disturbing noises to refrain from masking allowsthat subject's individual sensitivities and preferences to be taken intoconsideration, permitting the subject to tailor the dynamic masking asdesired.

Such input from the subject may be from a list of pre-selected options,a noise the subject records, or a noise known to occur around the sametime in the vicinity of the subject's sleeping environment. Thepre-selected options may be a list of noises that are known to eitherdisturb or not disturb sleep selected by a manufacture, disturbing ornon-disturbing noises recorded by the subject, or a list of disturbingor non-disturbing noises generated based on the location of thesubject's sleep environment. For instance, other users locatedgeographically near the subject's sleeping environment may upload orinput noises that were disturbing or non-disturbing to that user'ssleep. The subject may then browse the list of user-input noises andselect one or more noises the subject predicts will disturb their sleepto mask, or one or more noises the subject predicts will benon-disturbing noises to refrain from masking. In another example, thesubject may input, select, or download a schedule of known sleepdisturbing noises, such as a train or flight schedule if the subject'ssleeping environment is located near train tracks, a train station, anairport, a bus route, etc.

At 406, one or more biosignal parameters of a subject are measured. Thebiosignal parameters may be measured or monitored using a biosensor,such as the biosensor 312 of FIG. 3. The one or more biosignalparameters may comprise at least one of: a heart rate, heart ratevariability, respiration rate, EEG, EOG, EMG, motion of the subject, orother suitable parameters. One or more values of the biosignalparameters may be indicative of a sleep condition or sleep physiology ofthe subject over a time period. Based on the sleep condition orphysiology, an arousal threshold may be determined. The sleep conditionor physiology may be determined based on one or more of personalizedsleep data or historical sleep data collected using a subset of society,or both.

In at least one example, the one or more biosignal parameters of thesubject are monitored over a time period and analyzed to collecthistorical sleep data of the subject. For example, the subject'sbiosignal parameters may be measured every time the subject sleeps inthe sleeping environment for several days, such as a week or a month.The subject's biosignal parameters may be analyzed via a learningalgorithm each time the biosignal parameters are measured or uploaded.The analyzed biosignal parameters may provide information regarding thesubject's threshold to different kinds of environmental noises ormasking sounds, allowing the dynamic masking to be uniquely tailored orfine-tuned to the subject. The analyzed biosignal parameters may furtherprovide information regarding the subject's sleep patterns, such aswaking or sleep stage cycles or reoccurring events taking place atapproximately the same time during a subject's sleep cycle, which may beused to help predict when environmental noises will disturbing thesubject's sleep. Additionally, the historical sleep data of the subjectmay be used in combination with the historical environmental noise datagathered in operation 402 and/or with the input received in operation404. Thus, the subject's unique stages of sleep relative to differentsounds in the sleeping environment may be taken into consideration.

At 408, a timing of when the potentially disturbing noises will occur ispredicted. Predicting the timing of when the potentially disturbingnoises will occur may be based on the determined reoccurring noises ofoperation 402 or on the input of operation 404. Additionally, predictingthe timing may include predicting a pattern, interval, frequency, volumeor decibel level, and/or onset/offset of the potentially disturbingnoise. Predicting the timing of the potentially disturbing noisesenables the potentially disturbing noises to be anticipated, and assuch, enables the masking noise to be dynamic. In an aspect, thepotentially disturbing noises are predicted to have already begun, inwhich case method 400 proceeds to 410.

At 410, a prediction of when a noise will disturb the subject's sleep ismade based on the predicted timing of the potentially disturbing noisesand the measured one or more biosignal parameters. The prediction may befurther based on the sleep condition of the subject and the historicalsleep data of the subject. As described above with reference to FIG. 1,a subject's sleep condition is used to predict the likelihood thesubject's sleep may be disrupted, and the effect of environmental noiseson a sleeping subject varies based on the subject's sleep condition.Thus, depending on the biosignal parameters and the sleep condition, anenvironmental noise may be predicted to be a non-disturbing at one time,but as a disturbing noise at another time. If a noise is not predictedto be a sleep disturbing noise, the noise is identified as anon-disturbing noise, and method 400 proceeds to 412. At 412, a maskingsound is refrained from being output in anticipation of the identifiednon-disturbing noise. In one embodiment, the masking sound is refrainedfrom increasing in volume, but may continue to be output at a lowervolume or level when noises are identified as non-disturbing.

If a noise is predicted to disturb the subject's sleep, method 400proceeds to 414. At 414, a masking sound is dynamically adjusted basedon the parameters of the predicted disturbing noises and the measuredone or more biosignal parameters. The masking sound may further beadjusted based on the sleep condition of the subject, the arousalthreshold, and/or the historical sleep data of the subject. Adjustingthe masking sound may comprise adjusting a masking sound that is alreadybeing output in the sleeping environment, or adjusting or setting theparameters of a masking sound that is to be output in the sleepingenvironment. Adjusting the masking sound may comprise adjusting at leastone of: a spectral content of the masking sound or a SPL of the maskingsound. Adjusting the masking noise may further include adjusting thefrequency, volume, timing, and rate of the masking sound. For example,if the disturbing noise is relatively quiet, such as around 40 dB, andthe subject is in a deep sleep stage, such as stage N3 sleep, themasking noise may be adjusted to a lower volume to compensate for thedisturbing noise. Thus, even if the same predicted disturbing noiseoccurs at the same time every night, the masking noise output may bedifferent depending on the biosignal parameters, the sleepcondition/arousal threshold of the subject at that particular time, anddata learned or gathered via the learning algorithm.

At 416, the adjusted masking sound is output prior to or concurrentlywith the predicted disturbing sound occurring. A speaker may be used tooutput the adjusted masking sound, such as the audio output transducer308 of FIG. 3. The speaker may be configured to gradually increaseoutputting the masking sound prior to the predicted disturbing noiseoccurring, and to gradually decrease outputting the masking sound afterthe predicted disturbing noise has ceased. The speaker may be furtherconfigured to dynamically and continuously adjust the output of themasking noise if the disturbing noise is a fluctuating, oscillating, orpulsating noise. The speaker may be further configured to output themasking sound immediately prior to or concurrently with the occurrenceof the predicted disturbing noise. For example, if a predicteddisturbing noise starts off quietly and becomes louder, such as apassing train, the speaker may be configured to output the masking soundimmediately prior to or concurrently with the predicted disturbing noisebeginning. The speaker may be further configured to dynamically andcontinuously adjust the output of the masking noise in response todisturbing noises occurring in real-time in the sleeping environment,such as adjusting the masking noise in response to a changing volume orfrequency of the disturbing noise.

By utilizing the method and apparatus described above for dynamicallyand proactively masking potential sleep disturbing noises in a sleepingenvironment, a subject's sleep may be regulated and/or protected byreducing sleep disruptions. Adjusting a masking noise based on theparameters of the predicted disturbing noise and the subject's biosignalparameters allows the masking to be individually and uniquely tailoredto the needs of the subject. Furthermore, dynamically maskingenvironmental noises prior to or concurrently with the occurrence of thepredicted disturbing noise enables the noise to be masked in anefficient and effective manner.

According to aspects, methods of protecting sleep are cut off or stoppedbased on a subject's selections. The subject may select one or moresounds, notices, or alerts which are not to be masked, or which are tobe identified as non-disturbing noises. For example, the subject maywish to hear fire alarms, security system notifications, a phoneringing, a crying baby, a doorbell, and/or any other audiblenotification or alarm. The subject may program the audio device or audiosystem to recognize these desired sounds. The audio device or audiosystem may refrain from masking these detected sounds or from applyingANR in the presence of these detected sounds.

According to aspects, the subject may program the audio device or audiosystem to recognize undesired sounds which may be specific to thesubject's environment. In an example, the subject may program the audiodevice or audio system to recognize a crying baby, a snoring companion,or garbage trucks. The audio device or audio system may mask ornoise-cancel (in examples, partially noise-cancel) these detectedsounds.

According to an aspect, the desired and undesired sounds may beprogrammed by any combination of selecting these sounds from a libraryor recording real-life examples of the sounds for input to the audiodevice or audio system. The subject may categorize sounds asdesired/non-disturbing or undesired/disturbing. The audio device oraudio system is configured to analyze components of the ambient noise toidentify the selected sounds and categorize them as desired or undesiredsounds based on the subject's selections. The audio device or audiosystem masks the undesired sounds or applies a higher level of ANR forundesired sounds and does not mask the desired sounds or applies a lowerlevel of ANR for desired sounds. Accordingly, selected portions of theambient noise are selectively masked or are not masked.

In addition to categorizing sounds as desired and undesired, the subjectcan identify sounds that should be enhanced. For example, a subject mayneed to hear a crying baby or any other audible notification or alarm atcertain times. The subject may program the audio device or audio systemto recognize these sounds and enhance them upon detection.

In the preceding, reference is made to aspects presented in thisdisclosure. However, the scope of the present disclosure is not limitedto specific described aspects. Aspects of the present disclosure maytake the form of an entirely hardware embodiment, an entirely softwareembodiment (including firmware, resident software, micro-code, etc.) oran embodiment combining software and hardware aspects that may allgenerally be referred to herein as a “component,” “circuit,” “module” or“system.” Furthermore, aspects of the present disclosure may take theform of a computer program product embodied in one or more computerreadable medium(s) having computer readable program code embodiedthereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples of a computer readable storage medium include: anelectrical connection having one or more wires, a hard disk, a randomaccess memory (RAM), a read-only memory (ROM), an erasable programmableread-only memory (EPROM or Flash memory), an optical fiber, a portablecompact disc read-only memory (CD-ROM), an optical storage device, amagnetic storage device, or any suitable combination of the foregoing.In the current context, a computer readable storage medium may be anytangible medium that can contain, or store a program.

The flowchart and block diagrams in the figures illustrate thearchitecture, functionality and operation of possible implementations ofsystems, methods and computer program products according to variousaspects. In this regard, each block in the flowchart or block diagramsmay represent a module, segment or portion of code, which comprises oneor more executable instructions for implementing the specified logicalfunction(s). In some implementations the functions noted in the blockmay occur out of the order noted in the figures. For example, two blocksshown in succession may, in fact, be executed substantiallyconcurrently, or the blocks may sometimes be executed in the reverseorder, depending upon the functionality involved. Each block of theblock diagrams and/or flowchart illustrations, and combinations ofblocks in the block diagrams and/or flowchart illustrations can beimplemented by special-purpose hardware-based systems that perform thespecified functions or acts, or combinations of special purpose hardwareand computer instructions.

1. A method for regulating a sleep pattern of a subject, comprising:analyzing a stored history of at least one biosignal parameter of thesubject over a period of time and environmental noises over the periodof time; determining timings of sleep disruptions of the subject based,at least in part, on the stored history of the at least one biosignalparameter of the subject over the period of time and the environmentalnoises over a period of time; obtaining a current measurement of the atleast one biosignal parameter of the subject; predicting, using thedetermined timings of sleep disruptions of the subject and the currentmeasurement of the least one biosignal parameter, whether a potentiallydisturbing noise will disturb the subject based on a similarity betweenthe potentially disturbing noise and the environmental noises; andoutputting a masking sound to maintain a current sleep condition basedon the analyzing of the stored history prior to an occurrence of thepredicted disturbing noise.
 2. The method of claim 1, furthercomprising: upon determining the potentially disturbing noise will notdisturb the subject, either refraining from outputting the masking soundor refraining from increasing a volume of a masking sound that iscurrently being played to the subject.
 3. The method of claim 1,wherein: the analyzing comprises analyzing the stored history of the atleast one biosignal parameter of the subject over the period of time andthe environmental noises over the period of time to determine how thesubject reacted to decibel levels, frequencies, and a recorded timing ofthe environmental noises; and the predicting comprises, using thedetermined timings of sleep disruptions of the subject and the at leastone biosignal parameter, to predict whether the potentially disturbingnoise will disturb the subject based on the obtained current measurementof the of the at least one biosignal parameter and the potentiallydisturbing noise having similar values to the decibel levels, thefrequencies, and the recorded timing.
 4. The method of claim 1, whereinadjusting the masking sound to maintain the current sleep condition ofthe subject and prevent disruption by the potentially disturbing noisecomprises: output the masking sound immediately prior to an occurrenceof the predicted disturbing noise.
 5. The method of claim 1, whereinoutputting a masking sound to maintain the current sleep conditioncomprises gradually increasing the masking sound over a first timeperiod prior to the potentially disturbing noise, and graduallydecreasing the masking sound over a second time period after thepotentially disturbing noise has stopped.
 6. The method of claim 1,further comprising: receiving, from the subject, at least one knowndisturbing noise to mask prior to outputting the masking sound.
 7. Anon-transitory computer-readable medium storing instructions which whenexecuted by at least one processor on an audio output device cause theaudio output device to perform a method comprising: analyzing a storedhistory of at least one biosignal parameter of a subject over a periodof time and environmental noises over the period of time; determiningtimings of sleep disruptions of the subject based, at least in part, onthe stored history of the at least one biosignal parameter of thesubject over the period of time and the environmental noises over aperiod of time; obtaining a current measurement of the at least onebiosignal parameter of the subject; predicting, using the determinedtimings of sleep disruptions of the subject and the current measurementof the least one biosignal parameter, whether a potentially disturbingnoise will disturb the subject based on a similarity between thepotentially disturbing noise and the environmental noises; andoutputting a masking sound to maintain a current sleep condition basedon the analyzing of the stored history prior to an occurrence of thepredicted disturbing noise.
 8. The computer-readable medium of claim 7,further comprising: upon determining the potentially disturbing noisewill not disturb the subject, either refraining from outputting themasking sound or refraining from increasing a volume of a masking soundthat is currently being played to the subject.
 9. The computer-readablemedium of claim 7, wherein: the analyzing comprises analyzing the storedhistory of the at least one biosignal parameter of the subject over theperiod of time and the environmental noises over the period of time todetermine how the subject reacted to decibel levels, frequencies, and arecorded timing of the environmental noises; and the predictingcomprises, using the determined timings of sleep disruptions of thesubject and the at least one biosignal parameter, to predict whether thepotentially disturbing noise will disturb the subject based on theobtained current measurement of the of the at least one biosignalparameter and the potentially disturbing noise having similar values tothe decibel levels, the frequencies, and the recorded timing.
 10. Thecomputer-readable medium of claim 7, wherein adjusting the masking soundto maintain the current sleep condition of the subject and preventdisruption by the potentially disturbing noise comprises: output themasking sound immediately prior to an occurrence of the predicteddisturbing noise.
 11. The computer-readable medium of claim 7, whereinoutputting a masking sound to maintain the current sleep conditioncomprises gradually increasing the masking sound over a first timeperiod prior to the potentially disturbing noise, and graduallydecreasing the masking sound over a second time period after thepotentially disturbing noise has stopped.
 12. The computer-readablemedium of claim 7, wherein the instructions further cause the audiooutput device to: receive, from the subject, at least one knowndisturbing noise to mask prior to outputting the masking sound.
 13. Anaudio output device comprising: at least one processor; and memorycoupled to the at least one processor, the memory including codeexecutable by the audio output device to: analyze a stored history of atleast one biosignal parameter of a subject over a period of time andenvironmental noises over the period of time; determine timings of sleepdisruptions of the subject based, at least in part, on the storedhistory of the at least one biosignal parameter of the subject over theperiod of time and the environmental noises over a period of time;obtain a current measurement of the at least one biosignal parameter ofthe subject; predict, using the determined timings of sleep disruptionsof the subject and the current measurement of the least one biosignalparameter, whether a potentially disturbing noise will disturb thesubject based on a similarity between the potentially disturbing noiseand the environmental noises; and output a masking sound to maintain acurrent sleep condition based on the analyzing of the stored historyprior to an occurrence of the predicted disturbing noise.
 14. The audiooutput device of claim 13, wherein upon determining the potentiallydisturbing noise will not disturb the subject, the memory furtherincludes code executable by the at least one processor to cause theaudio output device to either refrain from outputting the masking soundor refrain from increasing a volume of a masking sound that is currentlybeing played to the subject.
 15. The audio output device of claim 13,wherein: the analyzing comprises analyzing the stored history of the atleast one biosignal parameter of the subject over the period of time andthe environmental noises over the period of time to determine how thesubject reacted to decibel levels, frequencies, and a recorded timing ofthe environmental noises; and the predicting comprises, using thedetermined timings of sleep disruptions of the subject and the at leastone biosignal parameter, to predict whether the potentially disturbingnoise will disturb the subject based on the obtained current measurementof the of the at least one biosignal parameter and the potentiallydisturbing noise having similar values to the decibel levels, thefrequencies, and the recorded timing.
 16. The audio output device ofclaim 13, wherein in order to adjust the masking sound to maintain thecurrent sleep condition of the subject and prevent disruption by thepotentially disturbing noise, the memory further includes codeexecutable by the at least one processor to cause the audio outputdevice to: output the masking sound immediately prior to an occurrenceof the predicted disturbing noise.
 17. The audio output device of claim13, wherein in order to output a masking sound to maintain the currentsleep condition, the memory further includes code executable by the atleast one processor to cause the audio output device to graduallyincreasing the masking sound over a first time period prior to thepotentially disturbing noise, and gradually decreasing the masking soundover a second time period after the potentially disturbing noise hasstopped.
 18. The audio output device of claim 13, wherein the memoryfurther includes code executable by the at least one processor to causethe audio output device to: receive, from the subject, at least oneknown disturbing noise to mask prior to outputting the masking sound.